Excel is not only commodity spreadsheet it is also a powerful development platform. You can develop
VBA custom applications where the user can't see the underlying application (Excel).

Excel can help to solve problems quicker then with a standalone procedural language or an expensive
application such as Matlab or Mathematica. Since Excel has such advanced computational capabilities
and is ubiquitous in offices and homes, it would make sense to learn the capabilities of this application.

While this product is marketed by Microsoft as user-oriented, but in reality it has "professional"
capabilities. and is suitable for solving wide range of numerical problem and can perform pretty complex
financial simulations including simple statistical analysis tasks such as correlating data.

You can also perform curve fitting and regression, solve equations, perform integration and differentiation,
and solve both ordinary and partial differential equations. Some linear programming optimization tasks
also can be done with Excel.

There are tremendous amount of high quality books written about Excel including a dozen of books
from O'Reilly who now wants to get a peace of this lucrative market. But there are also tremendous amount
of low quality books and some of them are rated pretty highly on Amazon (lemmings effect ;-)

Spreadsheet applications were the killer application that drove the personal computer market. In
the early PC days, Lotus 1-2-3 (long with WordPerfect) dominated the productivity software business.

It's probably a safe bet that there's more data stored in Excel spreadsheets than in all the world's
databases.

Excel's Data menu offers basic database features, such as sorting, filtering, validation, and data-entry
forms. You can quickly import and export data in a variety of formats, including those of database management
applications, such as Access. The need for macro-programming in VBA become apparent as soon as you
need for entering, manipulating, and reporting data grow beyond the spreadsheet's basic row-column metaphor.

In cases Excel power is not enough moving to a relational database management system (RDBMS), such
as Access might be appropriate. The latter makes creating pretty complex databases with multiple linked
tables quick and easy. It also contains Query by Example wizard (called called Query Design view).
Access 2003 and 2007 has a collection of wizards to lead you step-by-step through each process involved
in developing and using a production-grade database application.

The first step is Excel macro programming is creation of user-defined functions (UDF). Excel makes
the creations of UDF really easy and such functions can be a valuable addition to set of standard functions.
See

This book is aimed at a level slightly higher than the total beginner. On page one, for instance
he assumes that you understand the statement SUM(A5000:A5049) means. Then he points out that
writing SUM(USSales) would make it easier to understand. He then describes how to name a range
of cells -- Not exactly what I'd call advanced, but certainly above novice.

The first third, or so, of the book is on these kinds of slightly advanced procedures that
you could get out of several Excell books. After that he kind of turns the approach around to
things like "Estimating a Demand Curve." This is looking for what you want to do rather than
just looking at a technique within Excell.

Many of his chapters have fairly sophisticated subjects, "Incorporating Qualitative Factors
into Multiple Regression." In this chapter he then looks at multiple factors that might go into
predicting things like predicting sales, predicting the Presidential race - with fairly surprising
results.

In a couple of chapters he has a bit of fun, i.e. Chapter 73 is "Picking Your Fantasy Football
Team."

Excell is quite a powerful package. It can be used for a lot of things beyond just filling
out an expense account. In this book a lot of non traditional uses are described in a very light
but informative manner. It is a very well done book.

This is an eclectic collection of various recipies for Excel. This is a strange "lemmings" effect
that the book has such a high rating on Amazon.

The book is essentially a badly written cookbook as it does not provide underling mechanics and
key ideas behind the Excel formulas. Chapters are more or less disconnected and most of them can
be read in any order.

At the end the reader is left with very new good findings that probably are not worth the price
of the book.

Pagecount is very deceptive -- considerable part of the book is fluff -- brainless reproduction
of basic things that one can find in help and that is not worth even one dollar. Many examples are
very trivial and not worth reading.

Tricks like Appendix B are simply disgusting -- the author just copied the listing of functions
that has no practical value whatsoever to inflate the pagecount.

Explanations mostly are extremely fuzzy. The author has real talent to make simple things complex
and complex things impossible. Also this is just "do like I said" type of cookbook: the author never
tries to explain concepts that are used (use of absolute adressing vs relative, the syntax intricacies
of the second argument of countif and similar functions, etc)

Also the book suffers from frequent references to previous versions of Excel, which only distract
the reader. One can assume that if the reader really wants to use one of the previous versions of
Excel he can buy prev. edition of the book and save money.

In few places were things became more interesting they are also incomplete and/or incorrect (creation
of your own VBA functions and collection of functions, usage of array functions like frequency,
etc).

My impression is the author is just a book writer and does not have rich real world experience
with Excel, the experience that is necessary to distinguish between important and trivial things.

As a result he cannot provide the reader any help in getting the grasp of underling architectural
ideas, that are often very non-trivial (Excel is extremely powerful analytical tool disguised as
a commodity spreadsheet).

A friend brought to my attention another example of how Excel may actually be a precursor of
Skynet, after the
London
Whale trade and the
Reinhart-Rogoff
controversy. This comes to us in a research note from several years ago by several bioinformatics
researchers titled “Mistaken
Identifiers: Gene name errors can be introduced inadvertently when using Excel in bioinformatics.”
The problem is that various genes have names like “DEC1″ or identifiers like “2310009E13.” When
you important those text strings into Excel, by default, the former is converted into a date and
the later is converted into scientific notation (2.310009 x 10^13). Since dates in Excel are really
numbers behind the scenes (beginning with January 1, 1900), those text identifiers have been irretrievably
converted into numbers.

This problem is related to what makes Excel so popular: it’s powerful, intuitive, and easy to
use. In this case, it is guessing at what you really mean when you give it data in a certain format,
and most of the time it’s right—which saves you the trouble of manually parsing text strings and
converting them into dates (which you can do using various Excel functions, if you know how). But
the price of that convenience is that it also makes it very easy to make mistakes, if you don’t
know what you’re doing or you’re not extremely careful.

There are workarounds to this problem, but as of 2004, it had infected several public databases.
As the authors write, “There is no way to know how many times and in how many laboratories the default
date and floating point conversions to non-gene names have adversely affected an experiment or caused
genes to ‘disappear’ from view.”

The Importance of Excel

I spent the past two days at a
financial regulation conference in Washington (where I saw more BlackBerries than I have seen
in years—can’t lawyers and lobbyists afford decent phones?). In his remarks on the final panel,
Frank Partnoy mentioned something I missed when it came out a few weeks ago: the role of Microsoft
Excel in the “London Whale” trading debacle.

The issue is described in the appendix to JPMorgan’s internal investigative
task force’s report. To summarize: JPMorgan’s Chief Investment Office needed a new value-at-risk
(VaR) model for the synthetic credit portfolio (the one that blew up) and assigned a quantitative
whiz (“a London-based quantitative expert, mathematician and model developer” who previously worked
at a company that built analytical models)
to create it. The new model “operated through a series of Excel spreadsheets, which had to be completed
manually, by a process of copying and pasting data from one spreadsheet to another.” The internal
Model Review Group identified this problem as well as a few others, but approved the model, while
saying that it should be automated and another significant flaw should be fixed.** After the London
Whale trade blew up, the Model Review Group discovered that the model had not been automated and
found several other errors. Most spectacularly,

“After subtracting the old rate from the new rate, the spreadsheet divided by their sum instead
of their average, as the modeler had intended. This error likely had the effect of muting volatility
by a factor of two and of lowering the VaR . . .”

I
writeperiodically
about the perils of bad software in the business world in general and the financial industry
in particular, by which I usually mean back-end enterprise software that is poorly designed, insufficiently
tested, and dangerously error-prone. But this is something different.

Microsoft Excel is one of the greatest, most powerful, most important software applications of
all time.** Many in the industry will no doubt object. But it provides enormous capacity to do quantitative
analysis, letting you do anything from statistical analyses of databases with hundreds of thousands
of records to complex estimation tools with user-friendly front ends. And unlike traditional statistical
programs, it provides an intuitive interface that lets you see what happens to the data as you manipulate
them.

As a consequence, Excel is everywhere you look in the business world—especially in areas where
people are adding up numbers a lot, like marketing, business development, sales, and, yes, finance.
For all the talk about end-to-end financial suites like SAP, Oracle, and Peoplesoft, at the end
of the day people do financial analysis by extracting data from those back-end systems and shoving
it around in Excel spreadsheets. I have seen internal accountants calculate revenue from deals in
Excel. I have a probably untestable hypothesis that, were you to come up with some measure of units
of software output, Excel would be the most-used program in the business world.

But while Excel the program is reasonably robust, the spreadsheets that people create with Excel
are incredibly fragile. There is no way to trace where your data come from, there’s no audit trail
(so you can overtype numbers and not know it), and there’s no easy way to test spreadsheets, for
starters. The biggest problem is that anyone can create Excel spreadsheets—badly. Because it’s so
easy to use, the creation of even important spreadsheets is not restricted to people who understand
programming and do it in a methodical, well-documented way.***

This is why the JPMorgan VaR model is the rule, not the exception: manual data entry, manual
copy-and-paste, and formula errors. This is another important reason why you should pause whenever
you hear that banks’ quantitative experts are smarter than Einstein, or that sophisticated risk
management technology can protect banks from blowing up. At the end of the day, it’s all software.
While all software breaks occasionally, Excel spreadsheets break all the time. But they don’t tell
you when they break: they just give you the wrong number.

There’s another factor at work here. What if the error had gone the wrong way, and the model
had incorrectly doubled its estimate of volatility? Then VaR would have been higher, the CIO wouldn’t
have been allowed to place such large bets, and the quants would have inspected the model to see
what was going on. That kind of error would have been caught. Errors that lower VaR, allowing traders
to increase their bets, are the ones that slip through the cracks. That one-sided incentive structure
means that we should expect VaR to be systematically underestimated—but since we don’t know the
frequency or the size of the errors, we have no idea of how much.

Is this any way to run a bank—let alone a global financial system?

* The flaw was that illiquid tranches were given the same price from day to day rather than being
priced based on similar, more liquid tranches, which lowered estimates of volatility (since prices
were remaining the same artificially).

** But, like many other Microsoft products, it was not particularly innovative: it was a rip-off
of Lotus 1-2-3, which was a major improvement on VisiCalc.

*** PowerPoint has an oft-noted, parallel problem: It’s so easy to use that people with no sense
of narrative, visual design, or proportion are out there creating presentations and inflicting them
on all of us.

Update 2/10: There is an interesting follow-on discussion that includes a lot
of highly-informed technical people, including some who work in finance, over at
Hacker News.

35 Responses to The Importance of Excel

I think there is a more fundamental problem, the model distorts the nature of the reality. Back
in the late 80s i spent a summer in one of NY’s largest real estate firms. At the time spreadsheets
were relatively new. My boss observed that the spreadsheet made people think that real estate was
a bond and not rewal estate.

In my opinion, if a ‘model devoloper’ has left to his users the possibility to copy and paste
or something like that, he did a bad job. With my work, I use Excel spreadsheets every day but when
I start to develop a project, I have in my mind a system with an engine (the spreadsheet with formulas
and macros) and with an user interface, with icons that prevent at users to do anything not provided.
So, the core of the spreadsheet can work without modications, and results can be more reliable.

Blackberries are preferred because of the enhanced security of RIM’s proprietary enterprise e-mail
capabilities. It’s how you know who’s dealing with potentially “sensitive” information in DC. That,
and legacy systems are slow to upgrade.

I am a professional software engineer, and what I design and build works because I know what
I’m doing. I have no sympathy for any of this. Programming IS an extreme sport. Leave it to the
professionals, and do NOT attempt it yourself at home.

” Errors that lower VaR, allowing traders to increase their bets, are the ones that slip through
the cracks. That one-sided incentive structure means that we should expect VaR to be systematically
underestimated . . ..”

This. A thousand times, this.

They’d probably use Ouija boards if they justified high-risk/high-reward strategies. ;)
After all, what happened to ratings agencies that dared to call crap “crap?”

As a software enginner what you describe is all too common. Excel is very powerful because it
is relatively easy to use, but its ease of use means anybody can write a program using the tool
which can be very difficult to understand or test.

What amazes me that the model was not tested more thoroughly considering the risks if there were
systematic errors in the calculations.

cubicamente – I agree, I follow the same logic. The users are dumb so prevent them from doing
anything other than what you build the tool to do. However, to James’ point, anyone can create a
spreadsheet, and their is no formal user acceptance testing, unit testing, stress testing, etc that
occurs with the normal SDLC. I have been stating for many years at my current employer that we should
not be running our business on an Excel spreadsheet, even when we run SAP. There is far to much
downside risk and limited upside from the productivity. Additionally, I think it makes people dumber
and less likely to critically think through situations.

I guess this is where python and its libraries come in. You can build reliable models using code.
Maybe its time the curriculum of mba/accounting/finance programs are also curated to add courses
in python and financial modelling instead of just the fin engineers and quants doing the modelling.

“The biggest problem is that anyone can create Excel spreadsheets—badly. Because it’s so easy
to use, the creation of even important spreadsheets is not restricted to people who understand programming
and do it in a methodical, well-documented way.” Unfortunately this is not only true for Excel and
Powerpoint but for other parts of common office suites as well. One of my pet peeves is text documents
where empty paragraphs are used to set paragraphs visually apart. Another one is the abundance of
ad hoc formatting which increases size of documents and makes them look odd.

There is a rich literature (accessible through Google Scholar) on the deficiencies of Excel for
ststistical calculation and the unwiilingness or inability of Microsoft to fix them. Much better
is the open source (and free) Excel clone, Gnumeric.

Well, I think it’s safe to say I’ve been one of the more loyal and LONGTIME readers of this site.
I joined in on the dialogue here after Simon’s first appearance on Bill Moyers. I wanna say that
was 2008, but if it wasn’t 2008 it was 2009. I gladly purchased both books, and I enjoyed them immensely
and learned a lot from them (I learned more from “13 Bankers” than from “Burning” but I walked away
with better understand and knowledge base from both).

But I think this will probably be my last post here. The “sweet spot” from Mike Konczal’s old
site (Rortybomb) really left after he went to the Roosevelt Institute. Konczal’s writing drastically
changed after that. And I’m afraid that time has come to this site as well. Too much time intervals
between posts, too many tease links to other sites where after years of loyalty to the two hosts
we get the crumbs from the paid sites tossed at us for increased link hits.

And frankly, too many phrases like this one I don’t remember seeing in this site’s early days:
“where I saw more BlackBerries than I have seen in years—can’t lawyers and lobbyists afford decent
phones?”
I suppose people would say I am being “hypersensitive” to be upset at such a small passing remark.
But class snobbery, and judging people on socio-economic issues was kind of what I had thought
this site was supposed to be fighting against, not encouraging. I don’t think James Kwak
would have written that in the first 6 months—1yr+ of when this site was at its best. So to me,
it’s like picking up a glass of what you thought was your favorite brand of soda pop, but when you
ran it on your tongue you found they had substituted the sugar with high fructose corn syrup, and
it just wasn’t the same.

When I think of Konczal repeating liberal talking points VERBATIM (not because they are
the best, but as if he phoned the ACLU and Berkley Liberal Arts Dept. before every post to see if
it was kosher) and James Kwak saying things like “where I saw more BlackBerries than I have seen
in years—can’t lawyers and lobbyists afford decent phones?” I think I am tasting the Dr. Pepper
with high fructose corn syrup and not the Dr Pepper with sugar (“Rortybomb” and James Kwak circa
2009—20??) that I liked so much.

Warm Regards,
Resentful and Bitter Zeitgeist crouching under the keyboard.

Dear Moses -
I’ve never commented on this blog before, but I always read what others have to say. I hope you
reconsider you decision to not continue making your ideas known on this blog. I, for one, look forward
to what you have to say.

Let me add to Moses Herzog’s critique: Your topic today, whether you know it or not, is a bookkeeping
problem/solution pattern. I discovered, 35 years ago, when I bought my first microprocessor-driven
computer, that it is impossible to create a proper double-entry book-of-accounts using any spreadsheet,
no matter how it is designed.

There are four fundamenta variables in a proper book-of-accounts: debtor-value, creditor-rights,
cash, and capital. Pacioli calls the bookkeepers attention to these four variables in 1494 A.D.
The four are isomorphically related to one another within the contract that the bookkeeping sets
out to resolve; read as “sets out to balance.”

Until these bookkeeping fundamentals are understood by the software community, and the accounting
software designers know how to create the four-way isomorphic balance by using a serious programming
language, the banks will continue to steal from the monetary system.

Right now, James, your above essay has no right to take up the bandwidth that you are wasting
by your not knowing where first base is located in the playing-field of software-driven accounting.

Actually, the real problem with PP is that it, at root, has no actual value at all. Anything
that can be communicated with PP can be communicated better with some other media: verbally, paper,
PDF, whatever. Heck, most presentations and meetings are really unnecessary.

I don’t use Excel except when I am required to. There’s several reasons for this. First off,
it’s ability to do complex mathematics is incredibly poor. If you’re not dealing with something
that was linear in the first place Excel is not the best program for it. If you’ve got phenomena
operating in opposing directions it’s not terrible if you can linearize them and run in very small
steps. But if you’ve got coupled equations that aren’t necessarily positively or negatively reinforcing,
Excel should be last on the list.

Second problem is documentation. Excel spreadsheets are notorious for being poorly documented.
Shoot, it’s difficult to see who came up with it in the first place, then you’ve got to comb through
the attached VBA and the cell formulas to find it.

Third, mobility of data. I’ve seen many instances where Excel doesn’t correctly or consistently
pull from a database or update the database correctly. It was certainly a matter of poor coding,
but Excel doesn’t seem to consistently write to databases from machine to machine.

What Excel is pretty good for is dumbed-down visualization, ie, when you’re presenting technical
stuff but need to make it ultra pedestrian for the business school guys, nothing’s better than Excel’s
cartoonish graphics.

@Moses, I have to agree with you. Baselinescenario was created to discuss the reasons behind
and way forward from the Crash of 2008-2009 and had its greatest relevancy then. Now, it’s mostly
a site waiting and hoping for something positive to happen in a political environment that has regrouped
and moved on in the same general direction it was heading before the crash. Simon and James have
spoken their peace, written their books, and are moving on as well. There needs to be a change in
national and Beltway politics that can reestablish a nexus of pragmatic governance for this site
to regain its vitality. I’m hoping that my child will see that day. I suspect I won’t.

I totally disagree with this disgusting comment!!! Excel has several powerful tools although
it’s solver function could be improved for non linear responses and coupled models with over 4 degrees
of freedom (a convergence issue). For after tax cash flow analysis (in Engineering Economics class),
I once programmed in Excel the entire IRS Depreciation schedule with just two inputs and a lot of
conditional logic. (I found an error in the published tables which they fixed.)
It does not do PDE’s which economists seem to love and practical engineers regard as oversimplifications
of reality since most of them ignore friction (economic parallel??). It doesn’t do computational
fluid dynamics either but we have good programs like Fluent which do. In addition to the wonderful
flow visualizations, they provide the data we need in spreadsheet format for further analysis.
I like Excel because I can check the individual calculations which are hidden by most programs.

By the way from what I have read, A program that excel basically copied, Lotus 1-2-3, was basically
the ‘killer app’ of personal computers which made forever changed accountants jobs for the better.
The PC revolution in the early 80′s took off from there. It that way the spreadsheet is the most
important application of all time.

I sympathize with Moses’s concerns. When statistics and numbers are manipulated to favor the
ruling classes agenda, and since we it has been proved that politicians, (at this point in time),
can no longer distinguish right from wrong, or right from the left, or anything other than the current
status quo. We really do have a dysfunctional congress, that takes money candidates over quality
ones. And we have a wall street that is in denial to it’s dying breath.
I myself don’t know how it can sustain itself, and had I the power, I would expose them all.
It’s really only a matter of time as to when, and how, the reset equation is used, so the strong
CAN carry on. Until then we must put up with disinformation politics, and economics, because it
has become the norm.

Blaming Excel is like blaming guns for gun crime. There are many technical ways to potentially
overcome the ‘copy and pasting’ problem. For example using templates, locked cells/sheets, Excel
Services, document-level customizations etc.

The problem described is NOT a technical one. Its social or organizational. What is it about
the banks and those they employ which allow casual and unprofessional ‘hacks’ to be built for mission
critical activity? Why don’t they know their tools well? Where is the training? Where is choosing
the right tool for the job? Where is the technical oversight and leadership?

Excel, Powerpoint and Access all suffer from similar issues – they are tools which are overused
by amateurs. What is described above for Excel is exactly the same sort of critique Tufte has of
Powerpoint – namely it creates a false sense of competence and is overused in places it should not
be in order to satisfy the gods of “convenience”.

I think so se sight of the original facts. The bank contracted out the building of a model to
an “expert” who made a programming error. I agree with the original post that it is too easy to
make such errors in Excel. Excel should probably not be used for production calculations but when
it is, the model should be properly tested and documented. I wonder what the state of the art is
for standards and tools to document and test spreadsheets. (VisiCalc was the original killer app
– Lotus 123 was a clone written for the IBM-PC)

I just discounted everything you wrote because of your hysterical and gratuitous Microsoft bashing.
By the way, Lotus had an innovative commanding system but still essentially ripped off VisiCalc
and Multiplan. Excel was the first with a GUI.

@David (professional software engineer): Your point concerning the importance of experience,
training, and competence is well taken. Having said that,…
With all due respect for your doubtless considerable expertise in building software that does the
work it is designed to do, please bear in mind this well established and humbling fact: Every human
being is subject to marvelously seductive illusions of attention, memory, confidence and knowledge.
Awareness of their existence and power immunizes none of us against these illusions. Self-deception
afflicts each of us, bar none.

“After subtracting the old rate from the new rate, the spreadsheet divided by their sum instead
of their average, as the modeler had intended. This error likely had the effect of muting volatility
by a factor of two and of lowering the VaR . . .” “As the modeler had intended”….what? The spreadsheet
didn’t do anything the modeler screwed up. Excel is singularly unimaginative and uncreative and
suffers from being able to do one linear thing at a time which undermines supposedly nice features
like Real TIme Data links etc. Oy a+b vs (a+b)/2…..or such.

Believing in Models in the first place is a far bigger error perhaps than misconstructing them…a
model allows humans to withdraw from responsibility for their actions. Models are
only models. Reality is far more complex than a model and the assumption a model captures reality
in a suitably complete manner to be the sole basis of decision making is stupid in itself.

In any case the dialogue set out above gets sucked into the bs of technical matters when in fact
there were some very obvious ‘non-technical’ matters that should have constrained the Whale or led
to his constraint by a supervisor (not a committee with no apparent singular person held accountable)
like an overall position limit for example which requires no VAR to ascertain and could easily have
been summed up on one or two sheets of an Excel workbook.

And so through technical arguments, critiques of spreadsheets, committees
we lose track of the fact that the Whale was out of control and no one is ultimately held responsible
in a significant way. Controlling unbridled corporate Banking Greed would go much further than quiblling
about models to prevent trading abuses – a class and moral approach to controlling criminal behavior.

...have an Excel table. Each row is a separate record. The user types in new records at the end
of the table. One of the columns in the table contains a formula. Ideally the formula should apply
for each cell in the entire column. Since I don't know how long the table will end up being, I simply
ask that the user drag the formula down from the cell above. I do not want the user to accidentally
change the formula though. At first I thought a Custom validation with a secret word that the user
is unlikely to type in, would keep the user from changing the formula already in the cell. However,
I can't stop the user from deleting the formula, which doesn't help. I then thought maybe locking
(protecting with password) the column would do the trick. However, now the user can't drag down
the formula from the cell above. I would therefor like help with one of 2 options:

1- have the
formula apply to the cell automatically as a new record is created (ideal)
2- find a way to protect the cell so that the user can copy the formula down, but not change or
delete it

Any brain waves?

I did find the following code online, which appears to go some ways to answer my first option,
though I can't figure out why it only works if the formula is in column A (i.e. I have formulas
in columns A, B, K, L, and AF to DL).

Option Explicit
Private Sub Worksheet_Change(ByVal Target As Range)
Dim r As Range, c As Range, t As Range
On Error Goto TheEnd
If Not Intersect(Target, [E9:E65536]) Is Nothing Then 'Skips B1. Titles usually on first 7 rows. Row 8 has first formulas. Column E has first user typed entry
MsgBox Intersect(Target, [E9:E65536]).Address & " was changed."
Application.EnableEvents = False
Application.Calculation = xlCalculationManual
Application. ScreenUpdating = False
For Each t In Target
Set r = Union(Range("A" & t.Row), Range("C" & t.Row, Cells(t.Row, 19)))
If VarType(t.Value) = vbEmpty Then
'r.ClearContents 'Clear all contents in row where B is empty.
For Each c In r 'Clear only formulas where B is set to empty.
If c.HasFormula Then c.Clear
Next c
Goto nextt
End If
For Each c In r
If c.Offset(-1, 0).HasFormula Then c.Offset(-1, 0).Copy c
Next c
nextt:
Next t
TheEnd:
Application.EnableEvents = True
Application.Calculation = xlCalculationAutomatic
Application.ScreenUpdating = True
End If
End Sub

Last edited by m.cain; 02-21-2008 at 07:02 PM. Reason: found possible code, though
not sure how to use

Here we present a huge collection of spreadsheet files which originally appeared on a CD which was
sent, free, to members of ATM. We have now negotiated permission to make them available here.

But, if you’re not a member, please consider joining ATM. Not only will you be supporting the further
development of resources such as these but you will also receive the other benefits of belonging
to one of the leading professional associations for mathematics educationalists.

ATM’s ICT publication is a CD of 16 programs especially designed to be used with any interactive
whiteboard or projector. The programs provide a variety of teaching opportunities for KS2, KS3 and
KS4 classrooms and because they are so flexible, almost all can be used at all these key stages.

The CD associated with this book contains sixteen interactive spreadsheets which have
been developed to pose interesting and challenging problems. The tasks, many of which are well known,
have been transferred to this format to help teachers offer learning opportunities to pupils that
help develop their skills of mathematical reasoning.

The files will work with Excel and most other spreadsheet applications.

The problems require little prior knowledge in terms of explicit mathematical content. The aim
is to provide problems that are challenging but accessible to students in the upper primary and
secondary age ranges. Most of the problems include a range of extension problems to challenge even
the most able.

The files are interactive so that as learners respond to the tasks and questions posed the next
tasks appear on the screen automatically. The teacher’s guide offers suggestions for further extension
and hints concerning solutions and proofs.

Today’s Tip
*Applying Colors to Maximum/Minimum Values in a List*
*To apply colors to maximum and/or minimum values:*
Rounding all the numbers in column A to zero decimal places, except for those
that have "5" in the first decimal place.
1. Select a cell in the region, and press Ctrl+Shift+* (in Excel 2003, press
this or Ctrl+A) to select the Current Region.
2. From the Format menu, select Conditional Formatting.
3. In Condition 1, select Formula Is, and type =MAX($F:$F) =$F1.
4. Click Format, select the Font tab, select a color, and then click OK.
5. In Condition 2, select Formula Is, and type =MIN($F:$F) =$F1.
6. Repeat step 4, select a different color than you selected for Condition 1,
and then click OK.
*Note:*
Be sure to distinguish between absolute reference and relative reference when
entering the formulas.
See screenshot for a sample
<http://www.exceltip.com/images/screenshots/295.gif>

By default, when you copy text from a different
program (such as Microsoft Word, Microsoft PowerPoint®, or even Microsoft Internet Explorer) and
paste it into an Excel cell, the original formatting comes along for the ride. Sometimes this leaves
you with a tiny little cell with GIGANTIC FORMATTING that you need to fix by hand.

The Paste Options button that looks like this:

pops up, and you can use it to keep the original formatting or to match the destination formatting
(that is, the formatting you've chosen for your cell). However, if you're like me (or want to be
like me — aren't you sweet), that is just too many steps if you know that you want to match the
formatting of the cell. This is especially true if you have a another program and keep your cell's
formatting

Select the text you want to pop into your Excel worksheet.

Press CTRL+C.

Switch back to Excel.Tip Hey! Now's a good time to use that shortcut I told you about in the first tip!

Double-click in the cell, and press CTRL+V.

It's like magic in a click (or two).

And so you have it. Five decent little tips to boost your skill level and keep your work humming
along. So start the music!

"We are what we repeatedly do. Excellence, then, is not an act, but a habit." — Aristotle

Lynda Morris, president of NicLyn Consulting Corp, an Internet-based
computer and network service company, often finds herself entering the same information or formulas
in different parts of a spreadsheet. Instead of typing data repeatedly, she creates drop-down menus
that save typing time. To create a drop-down menu:

•

Open a worksheet and label your menu (Days for example) in the top cell of a column.

•

Enter data (days of the week, in this case) in the cells below the label (such as A2
to A8).

•

Highlight the list, including the label.

•

Click the Insert menu, then click Name, and then Define.

•

In the box under Names in workbook you will see the name of the range (Days).
In the Refers to box, it should list "=Sheet1!" followed by the range (=Sheet1!$A$1:$A$8).

•

Click Add and then OK.

•

Select any cell or range of cells in which you want to enter data.

•

Click the Data menu and then Validation.

•

From the Allow drop-down menu, select List. In Source, type "="
and the name of your range (=Days). Make sure that the In-cell dropdown box is checked.

•

Click one of the cells you highlighted to see your drop-down menu. Choose the item you
want to enter in the active cell. Enter data from your list, in any order, in each of the
cells you selected.

About: Spreadsheet::WriteExcel is a Perl module which can be used to create native Excel
binary files. Formatted text and numbers can be written to multiple worksheets in a workbook. Formulas
and functions are also supported. It is 100% Perl and doesn't require any Windows libraries or a
copy of Excel. It will also work on the majority of Unix and Macintosh platforms. Generated files
are compatible with Excel 97, 2000, 2002, and 2003, and with OpenOffice and Gnumeric. An older version
also supports Excel 5/95.

Needing to finish my first Excel add-in, and frustrated by the incompleteness and obscurity
of MS's help system, I picked up this book after reading warm recommendations from readers of
earlier versions.

If you have never programmed Excel before, but have programmed a tiny bit in some other language,
and do not have great ambitions for software development, this might be a fine text. It is quite
readable and full of useful information. Walkenbach introduces VBA quickly, which is great,
but so quickly he forgets to say what most of the language constructs do. His approach to teaching
the Excel object model is to provide several fairly well written examples of little macros and
utilities, each one with a clear English explanation. Unfortunately, if the technique you need
does not appear in any of these examples, you are out of luck, because his explanations are
neither extensive, detailed, nor thorough enough to impart a good understanding of what is going
on. This, coupled with Excel's erratic behavior (mis-type a property name and watch your user
form mysteriously disappear, for instance), makes it very difficult to become independently
productive without spilling a lot of sweat and tears.

The book's strengths include the numerous and well-organized examples provided on the companion
CD; the occasional sidebar that offers first-hand knowledge of bugs, inconsistencies, and strange
design; fairly broad, if incomplete, coverage of the major aspects of Excel VBA programming;
and very clear indications of differences among various Excel versions (97, 2000, 2003 mainly).
Walkenbach is obviously an expert and has been so for a long time.

The weaknesses become apparent in contrasting this book with, say, Roman's text (O'Reilley).
Where Walkenbach gives a macro to display all the icons associated with the several thousand
Excel 'FaceId's, Roman publishes the complete table as an appendix. Where Walkenbach loosely
skims over the properties of many key objects, such as ranges and charts, Roman takes the time
to provide a terse but useful description of nearly every property, as well as a very illuminating
diagram of the object hierarchy. Where Walkenbach completely omits to describe how VBA works,
Roman actually offers a deeper explanation (showing how object references are arranged in memory,
for instance, and describing exactly how a for..next loop is executed). Boring stuff for some,
maybe, but a huge time saver for those who appreciate that the details matter. For someone who
either has a lot of programming experience, or who plans to develop more than toy utilities
or one-off apps in Excel VBA, Roman's approach is much more useful than Walkenbach's.

If Walkenbach is appropriate for your background and ambitions, then you will probably agree
it is a four- or five-star effort. Otherwise, you will likely be somewhat disappointed and,
like me, will quickly find yourself looking for another book.

It is often either inconvenient or financially unfeasible to solve every mathematical problem with
a standalone procedural language or an expensive application such as Matlab or Mathematica. Since
Excel has such advanced computational capabilities built into it and is ubiquitous in offices and
homes, it would make sense to mine this application for numerical problem solving techniques. Bourg
does a masterful job of presenting the tools available in Excel and showing the reader how to put
them to work to solve real world engineering and mathematical problems. First, he spends a couple
of chapters briefly going over Excel and its language VBA (Visual Basic for Applications). Next
he goes over some intermediate level tasks such as collecting and cleaning up data, charting including
3D charts, and statistical analysis tasks such as correlating data and generating random numbers.
Next Bourg moves into purely mathematical tasks such as working with discrete Fourier transforms,
manipulating matrices and vectors, as well as working with basic mathematical functions. Once you
have learned to use these mathematical tools in Excel, Bourg uses them to show you how to perform
curve fitting and regression, solve equations, perform integration and differentiation, and solve
both ordinary and partial differential equations. He even spends time on performing multivariable
calculus and the finite element method in Excel. Chapter 13, on optimization, was my favorite chapter.
Here, Bourg is actually getting into a little algorithm analysis and design via linear programming
and genetic algorithms. This chapter showed me some truly innovative uses of Excel. The final chapter
deviates from the scientific flavor of the book and concentrates on more traditional financial applications.
The writing is very accessible, the examples are clear and very creative, and the author does a
tremendous job of capturing the range of Excel's mathematical capabilities. Do not expect mathematical
theory in this book. Bourg assumes you already know how to set up a mathematical problem and that
you just need a computational platform and tools with which to perform your work. It is nice to
know I am not necessarily held hostage by Mathworks(maker of Matlab) every time I need to solve
a mathematical problem of any level of sophistication. Highly recommended. The table of contents
is as follows:
1. Using Excel
2. Getting Acquainted with Visual Basic for Applications
3. Collecting and Cleaning Up Data
4. Charting
5. Statistical Analysis
6. Time Series Analysis
7. Mathematical Functions
8. Curve Fitting and Regression
9. Solving Equations
10. Numerical Integration and Differentiation
11. Solving Ordinary Differential Equations
12. Solving Partial Differenby
Gerald Knight tial Equations
13. Performing Optimization Analyses in Excel
14. Introduction to Financial Calculations

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